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Article

Genetic Variability and Population Structure of the Potential Bioenergy Crop Miscanthus sinensis (Poaceae) in Southwest China Based on SRAP Markers

by
Gang Nie
1,
Xin-Quan Zhang
1,*,
Lin-Kai Huang
1,
Wen-Zhi Xu
1,
Jian-Ping Wang
2,
Yun-Wei Zhang
3,
Xiao Ma
1,
Yan-Hong Yan
1 and
Hai-Dong Yan
1
1
Grassland Science Department, Sichuan Agricultural University, Ya'an 625014, China
2
Agronomy Department, University of Florida, Gainesville, FL 32610, USA
3
Grassland Institute, China Agricultural University, Beijing 100193, China
*
Author to whom correspondence should be addressed.
Molecules 2014, 19(8), 12881-12897; https://doi.org/10.3390/molecules190812881
Submission received: 28 June 2014 / Revised: 12 August 2014 / Accepted: 13 August 2014 / Published: 21 August 2014
(This article belongs to the Section Molecular Diversity)
Browse Figures
Versions Notes

Abstract

:
The genus Miscanthus has great potential as a biofuel feedstock because of its high biomass, good burning quality, environmental tolerance, and good adaptability to marginal land. In this study, the genetic diversity and the relationship of 24 different natural Miscanthus sinensis populations collected from Southwestern China were analyzed by using 33 pairs of Sequence Related Amplified Polymorphism (SRAP) primers. A total of 688 bands were detected with 646 polymorphic bands, an average of 19.58 polymorphic bands per primer pair. The average percentage of polymorphic loci (P), gene diversity (H), and Shannon’s diversity index (I) among the 24 populations are 70.59%, 0.2589, and 0.3836, respectively. The mean value of total gene diversity (HT) was 0.3373 ± 0.0221, while the allelic diversity within populations (HS) was 0.2589 ± 0.0136 and the allelic diversity among populations (DST) was 0.0784. The mean genetic differentiation coefficient (Gst = 0.2326) estimated from the detected 688 loci indicated that there was 76.74% genetic differentiation within the populations, which is consistent with the results from Analysis of Molecular Variance (AMOVA) analysis. Based upon population structure and phylogenetic analysis, five groups were formed and a special population with mixed ancestry was inferred indicating that human-mediated dispersal may have had a significant effect on population structure of M. sinensis. Evaluating the genetic structure and genetic diversity at morphological and molecular levels of the wild M. sinensis in Southwest China is critical to further utilize the wild M. sinensis germplasm in the breeding program. The results in this study will facilitate the biofuel feedstock breeding program and germplasm conservation.

Graphical Abstract

1. Introduction

The genus Miscanthus is comprised of C4 perennial rhizomatous grasses, originated from Eastern Asia. Owing to high biomass productivity [1], low-nutrient input [2,3], and high water-use efficiencies [4], Miscanthus have attracted considerable attention as one of the most promising non-food bioenergy crops. There are about 10-15 Miscanthus species distributed worldwide, of which seven are native to China [5,6,7,8]. Since the 1970s, this genus, specifically M. × giganteus, has been intensively studied in Europe as a biomass feedstock [7,9,10]. However, M. × giganteus is propagated by plant rhizomes or tissue culture and does not produce fertile flowers or seeds, and its production is heavily limited by its natural sterility and a narrow genetic base [11]. As a progenitor of M. × giganteus, M. sinensis is propagated by seeds which is a favorable trait for crop adoption and provides a comparable yield in some places and could be a valuable genetic resource for biofuel crop domestication and improvement [6,12]. Based on the previous tests of drought and cold tolerance of M. sinensis in Europe, a much broader range of adaptation than M. × giganteus was found in this diploid species [1,11]. So with M. sinensis it is considered possible to breed varieties with similar or better yield but higher tolerance for frost and drought than M. × giganteus. Besides, it can be used in crosses to create new cultivars of M. × giganteus.
Molecular markers are essential tools for germplasm evaluation, genetic analysis, and marker-assisted breeding for crop improvement. Employing molecular markers, such as Sequence Related Amplified Polymorphism (SRAP), Amplified Fragment Length Polymorphism (AFLP), Inter-Simple Sequence Repeats (ISSR) and Simple Sequence Repeats (SSR) [13,14,15,16,17,18,19] to estimate genetic variation within species could assist the breeding program for parental and breeding line selection and desirable traits. SRAP is recognized as a new and useful molecular marker system because of its high reproducibility, low cost, and no requirement of prior knowledge of target sequences [20]. Up to now, SRAP markers have been successfully used for evaluation of genetic diversity for Carthamus tinctorius, Cucurbita pepo, buchloe dactyloides, and Solanum lycopersicon [21,22,23,24] and genetic map construction for Gossypium hirsutum and Triticum aestivum [25,26].
In recent years, many reports on Miscanthus were published showing the abundant resources distributed in China [12,27,28,29]. Zhao et al. and Clark et al. revealed the population structure of M. sinensis native to China using SSR and SNP makers respectively. Xu et al. used 20 pairs of EST-SSR makers of sorghum to analyze 26 populations of M. sinensis from Southwest China, indicating a high genetic diversity and the existence of a gene flow in M. sinensis populations in this area. However, the SSR markers used in that study were mainly derived from the non-coding regions, which may not be able to provide sufficient evidence to reveal the diversity and differentiation of M. sinensis in Southwest China; therefore, SRAP markers, derived from the coding region, were used in this study. Southwest China, as one of the 34 biodiversity hot spots around the World, has abundant wildlife resources [30]. It is crucial to evaluate the genetic structure and genetic diversity of the wild M. sinensis germplasm, which is widely distributed in Southwest China and to eventually utilize this valuable germplasm for crop improvement. However, there are no thorough studies on the genetic diversity and population structure of the germplasm distributed in Southwest China. Therefore, in this study, we evaluated the genetic diversity and population structure of 24 M. sinensis natural populations collected in Southwest China using SRAP markers to facilitate the conservation of the Miscanthus germplasm and breeding in the near future.

2. Results and Discussion

2.1. Polymorphism of SRAP Markers

Six accessions of M. sinensis, which have significant differences among the morphological characterization and geographic location, were selected to screen 100 pairs of SRAP primers. In total, 33 of them generated robust discernible bands (Table 1). These 33 SRAP primer pairs were then used to genotype the whole collection of 260 individuals. In total, 688 bands were generated and 646 (93.90%) were polymorphic. The number of bands per primer pairs ranged from 13 to 30, with an average of 20.58 bands, of which 19.58 in average were polymorphic. Primer pairs Me6 + em10 amplified the most number of polymorphic bands (30) while Me7 + em1 amplified the least number of polymorphic bands (9). The polymorphic information content (PIC) values ranged from 0.23 (Me3 + em5) to 0.41 (Me4 + em10) with a mean of 0.34, demonstrating a good discriminatory capacity (Table 1).

2.2. Genetic Diversity and AMOVA Analysis

The 24 wild distribution populations were comprised of 260 individuals which had a varied genetic diversity reflected by the three main genetic diversity parameters including percentage of polymorphic bands (P), Nei’s [31] gene diversity (H), and Shannon’s Information Index of Diversity (I). Among the 24 populations, the P value ranged from 21.22% (Pop12) to 84.30% (Pop15), with an average of 70.59%. The H value ranged from 0.0787 (Pop12) to 0.3052 (Pop15), with an average of 0.2589 at the population level. The variation trend of the I value was similar to the other two parameters, with an average of 0.3836 (Table 2). The total numbers of P, H and I were 93.90%, 0.3377 and 0.5032 within species, respectively. The genetic data exhibited a high level of genetic diversity within M. sinensis species from southwest China.
Table
Table 1. Primer sequences amplification information of the SRAP markers.
Table 1. Primer sequences amplification information of the SRAP markers.
Pirmer PairsSequence 5'→3'Total Number of BandsNumber of Polymorphic BandsPercentage of Polymorphic Bands (%)Polymorphic Information Content (PIC)
Me1 + em3TGAGTCCAAACCGGATA
GACTGCGTACGAATTGAC		1515100.000.33
Me1 + em8TGAGTCCAAACCGGATA
GACTGCGTACGAATTCTG		161381.250.34
Me1 + em10TGAGTCCAAACCGGATA
GACTGCGTACGAATTCAG		2121100.000.38
Me2 + em1GACTGCGTACGAATTTGC
GACTGCGTACGAATTAAT		2121100.000.39
Me2 + em9GACTGCGTACGAATTTGC
GACTGCGTACGAATTCGA		171482.350.28
Me2 + em10GACTGCGTACGAATTTGC
GACTGCGTACGAATTCAG		292896.550.40
Me3 + em5TGAGTCCAAACCGGAAT
GACTGCGTACGAATTACC		181583.330.23
Me3 + em9TGAGTCCAAACCGGAAT
GACTGCGTACGAATTCGA		181794.440.31
Me3 + em10TGAGTCCAAACCGGAAT
GACTGCGTACGAATTCAG		2424100.000.34
Me4 + em1TGAGTCCAAACCGGACC
GACTGCGTACGAATTAAT		1616100.000.28
Me4 + em7TGAGTCCAAACCGGACC
GACTGCGTACGAATTCAA		222195.450.35
Me4 + em9TGAGTCCAAACCGGACC
GACTGCGTACGAATTCGA		201890.000.29
Me4 + em10TGAGTCCAAACCGGACC
GACTGCGTACGAATTCAG		201995.000.41
Me5 + em2TGAGTCCAAACCGGAAG
GACTGCGTACGAATTTGC		211990.480.30
Me5 + em4TGAGTCCAAACCGGAAG
GACTGCGTACGAATTTGA		191789.470.31
Me5 + em8TGAGTCCAAACCGGAAG
GACTGCGTACGAATTCTG		2525100.000.38
Me5 + em10TGAGTCCAAACCGGAAG
GACTGCGTACGAATTCAG		2323100.000.33
Me6 + em7TGAGTCCAAACCGGTAA
GACTGCGTACGAATTCAA		181794.440.34
Me6 + em8TGAGTCCAAACCGGTAA
GACTGCGTACGAATTCTG		272385.190.25
Me6 + em10TGAGTCCAAACCGGTAA
GACTGCGTACGAATTCAG		3030100.000.38
Me7 + em1TGAGTCCAAACCGGTCC
GACTGCGTACGAATTAAT		13969.230.28
Me7 + em5TGAGTCCAAACCGGTCC
GACTGCGTACGAATTACC		242291.670.33
Me7 + em8TGAGTCCAAACCGGTCC
GACTGCGTACGAATTCTG		161593.750.33
Me7 + em10TGAGTCCAAACCGGTCC
GACTGCGTACGAATTCAG		242395.830.39
Me8 + em5TGAGTCCAAACCGGTGC
GACTGCGTACGAATTACC		2222100.000.37
Me8 + em7TGAGTCCAAACCGGTGC
GACTGCGTACGAATTCAA		191894.740.40
Me8 + em9TGAGTCCAAACCGGTGC
GACTGCGTACGAATTCGA		2323100.000.32
Me9 + em1TGAGTCCAAACCGGTAG
GACTGCGTACGAATTAAT		252496.000.33
Me9 + em5TGAGTCCAAACCGGTAG
GACTGCGTACGAATTACC		181688.890.36
Me9 + em8TGAGTCCAAACCGGTAG
GACTGCGTACGAATTCTG		171588.240.34
Me9 + em9TGAGTCCAAACCGGTAG
GACTGCGTACGAATTCGA		211990.480.36
Me10 + em1TGAGTCCAAACCGGTTG
GACTGCGTACGAATTAAT		222195.450.38
Me10 + em2TGAGTCCAAACCGGTTG
GACTGCGTACGAATTTGC		242395.830.38
Total 688646
Mean 20.8519.5893.270.34
Table
Table 2. Genetic diversity of M. sinensis wild populations.
Table 2. Genetic diversity of M. sinensis wild populations.
Population IdentitySample SizeHIP
Pop1150.27120.406277.91%
Pop2130.29390.435179.80%
Pop3120.28770.426177.76%
Pop4130.28520.423778.78%
Pop5110.27270.404273.98%
Pop680.25990.383068.46%
Pop7110.28490.420676.60%
Pop8100.27920.412774.71%
Pop980.27340.403573.11%
Pop10120.27990.413075.00%
Pop1190.25800.381970.06%
Pop1250.07870.116221.22%
Pop13150.27730.412277.91%
Pop1450.24800.362462.79%
Pop15180.30520.454084.30%
Pop16140.28280.420979.22%
Pop17160.25910.391077.91%
Pop18110.27160.405276.45%
Pop1980.26790.393069.04%
Pop20150.27310.409078.49%
Pop21120.27080.402475.00%
Pop2260.23600.348462.65%
Pop2360.21140.311655.81%
Pop2470.18470.270047.24%
Mean 0.25890.383670.59%
Within Species2600.33770.503293.90%
Note: H, Nei’s gene diversity; P, Percentage of Polymorphic Bands; I, Shannon’s Information Index of Diversity.
The total gene diversity (HT) was 0.3373 ± 0.0221, while the gene diversity within populations (HS) was 0.2589 ± 0.0136 and the gene diversity among populations (DST) were 0.0784. The mean genetic differentiation coefficient (GST = 0.2326) estimated from the 688 bands indicated that there were 76.74% genetic variation within populations. These results demonstrated that the accessions had a higher level of genetic variation within populations than among them. The AMOVA analysis (Table 3) of the M. sinensis wild populations showed similar results that both the genetic variations within (86.0%) and among (14.0) populations were significant. In addition, there was a high frequency of gene flow (Nm = 1.6493) between populations, indicating there were more than one effective immigrants from one population into another at each generation.
Table
Table 3. AMOVA analysis of variance distribution with and amoung M. sinensis wild populations.
Table 3. AMOVA analysis of variance distribution with and amoung M. sinensis wild populations.
SourceDegree of FreedomSum of SquaresSummary of MatchesPercentage of Variation
Among Pops236468.464281.23814%
Within Pops23624162.059102.38286%
Total25930630.523100%
Miscanthus is widely distributed around the world, although its main distribution area or diversity center is in China [18,32]. Knowing the relationship and population structure of M. sinensis is important for their conservation and utilization [15]. In this study, the high level of genetic diversity of M. sinensis from southwest China was revealed by SRAP markers, which are similar to the previous results with EST-SSR, SSR and AFLP markers [9,12,18]. Meanwhile, SRAP analysis indicated higher genetic variation (76.74%) existed within populations than among populations, which is in agreement with the results in other grass species assessed by allozymes, ISSR, RAPD, SSR, and EST-SSR [12,33,34,35,36,37,38] and in M. sinensis of China assessed by SNP and SSR makers [18,32]. The main factors determining the plant population genetic structure include the mating and reproduction system, selection pressure, adaptation, and geographic locations [39]. The genetic recombination promotes genetic diversity within populations [40]. In plants, gene flow events can be initiated through pollen or seed. M. sinensis is an out-crossing species that can lead to a strong gene flow (Nm = 1.6493) and introgression among populations, so it is reasonable that the genetic variation within populations is greater than that among populations [41,42].

2.3. Population Structure and Cluster Analysis

The population structure of the 260 individuals was estimated under the Hardy-Weinberg Equilibrium by using STRUCTURE V2.3.3 software. Based on maximum likelihood and delta K (∆K) values, the number of optimum subgroups was five (Figure 1). By using a membership probability threshold (Q) of 0.60, majority of the individuals were clearly assigned to specific groups. Among them, 6 individuals were assigned to subgroup (SG) 1 with the accessions mainly collected from Pop24; 5 individuals to SG2 with the accessions mainly collected from Pop12; 27 individuals to SG3 with the accessions mainly collected from Pop13 and Pop15; 150 individuals to SG4 with the accessions mainly collected from Pop2, Pop3, Pop4, Pop5, Pop6, Pop7, Pop8, Pop9, Pop10, Pop11, Pop14, Pop18, Pop19, Pop21, Pop22, Pop23; 48 individuals to SG5 with the accessions mainly collected from Pop1, Pop16, Pop17 and Pop20; 24 individuals were retained in the admixed group (Table S1).
Molecules 19 12881 g001 550
Figure 1. Five subgroups of 260 M. sinensis accessions inferred from STRUCTURE analysis. The vertical coordinate of each subgroup indicates the membership coefficients for each individual. Red zone: SG1; Green zone: SG2; Blue zone: SG3; Yellow zone: SG4; Pink zone: SG5.
Figure 1. Five subgroups of 260 M. sinensis accessions inferred from STRUCTURE analysis. The vertical coordinate of each subgroup indicates the membership coefficients for each individual. Red zone: SG1; Green zone: SG2; Blue zone: SG3; Yellow zone: SG4; Pink zone: SG5.
Molecules 19 12881 g001
The genetic similarities (GS) of 260 individuals ranged from 0.565 to 0.972 with an average of 0.659 which showed a high level of genetic variation range among the accessions. The Un-weighted Pair-group Method with Arithmetic mean (UPGMA) dendrogram based on GS data obviously revealed that when at the genetic similarity coefficient value of 0.659, five major clusters were formed and group 1 accessions were mainly collected from the Yuxi area of Yunnan. The genotypes of group 2 were primarily collected from Zigong and Jian’ge in Sichuan. Group 3 contained mostly accessions from Jiangyou and Guangyuan. Group 4 accessions were mainly collected from Yaan, Daying, Banan and Zunyi (Figure S1). The rest of the accessions assigned to group 5. The results from the cluster analysis were similar with those from the structure analysis.
The genetic distances (GD) among the 24 populations were estimated by Nei’s [43] unbiased measure, which could obviously reveal the genetic relationship. The GD between Pop2 from Bifengxia and Pop3 from Baoxing was the lowest (0.028), and the distance between Pop12 from Zigong and Pop24 from Yuxi was the highest (0.292) with the mean of 0.097 (Table S2). The UPGMA dendrogram based on GD data clearly showed the relationships among the 24 populations (Figure 2), which was nearly congruent with the previous cluster analysis of 260 individuals. However, in this result, we found that a new group (Group 5) including Pop22 and Pop23 collected from Guizhou. Throughout the results of the two methods at different levels, we found that combining the analysis is the best strategy to reveal the genetic structure of M. sinensis in Southwestern China.
Molecules 19 12881 g002 550
Figure 2. Dendrogram of 24 M. sinensis populations based on GD data by UPGMA cluster analysis.
Figure 2. Dendrogram of 24 M. sinensis populations based on GD data by UPGMA cluster analysis.
Molecules 19 12881 g002
Apparently, Pop12 and Pop24 were differentiated from the other populations in both Structure and UPGMA analysis. The main reason could be the distinct geographic isolation between this two and the rest populations. In addition, Pop12 has the lowest genetic diversity parameters which are P (21.22%), H (0.0787), and I (0.1162), and a low gene flow exists between Pop12 and other populations. Furthermore, Pop12 has a narrow distribution range in this area and almost no other M. sinensis plants were found within a range of 5 km around it. Therefore, a habitat fragmentation was formed as influenced by founder effect.
Through the structure analysis, 14 out of 260 individuals with mixed ancestry were all from Pop16. In principle, all of the genetic material of the sampled individuals comes from one or more of K unobserved populations with each population characterized by a set of allele frequencies at each locus. When individuals have mixed ancestry, this means that each genotyped allele comes from one or more populations. We synthesized geographic information to analysis the accessions from Pop16 and found that they all collected along with the G42 highway in China which is the only entrance to the Dead Sea of China located in Da Ying County. The Dead Sea of China is a famous scenic spot where the total number of tourists is approximately 3 million per year. The huge traffic flow and the complex environment could help the seed spread widely. Hence a high gene flow occurred in this area and the plants there had a mixed ancestry. Although some researchers think these man-made factors contribute to the long term survival of populations, this is controversial [44], as several studies [45,46,47,48] indicate that they should not be neglected because those factors accelerate the loss of genetic variability through random genetic drift [49].
The previous clustering result of M. sinensis from southwest China assessed using SSR makers [12] was different from the dendrogram that resulted from SRAP makers. These differences could be due to the different DNA segment targets of SSR and SRAP makers. The SSR have a random distribution within the genome, while the target locus of SRAP is mainly in open reading frame regions [20,50]. SSRs mostly exists in non-genic regions, could be in genic regions as well, but with low frequency [50,51]. In different plant individuals, the number of repeat units varies, but the flanking sequence is conserved around the SSR. The numbers of loci studied and their coverage of the genome wide are important in obtaining reliable estimates of genetic relationships between populations and within population [52]. Although, both SRAP and SSR distinguished intraspecific taxa with similar great discriminating power, the average numbers of bands generated by each primer pair of SSR (14.80) [12] were much lower than that of SRAP (20.85). Therefore, we considered that SRAP was more efficient than SSR for assessing the genetic diversity of large numbers of M. sinensis accessions. In total, as widely used PCR-based markers, SRAP has advantages over SSR markers, since no prior knowledge of target sequences is required which make it to be widely utilized.

3. Experimental Section

3.1. Plant Material Collection

The experimental materials consisted of 260 individuals of M. sinensis collected from 24 natural populations in Sichuan, Chongqing, Guizhou, and Yunnan provinces in 2010 (Table 4).
The sampling locations were selected according to M. sinensis habitats based on geographic location and topography. All of approaches used in collecting samples are based on Xu’s method [12] (Figure 3). Within each population, the numbers of appropriate representative individuals were selected based on the size of each population.
Table
Table 4. Geographic information of the 24 populations of M. sinensis.
Table 4. Geographic information of the 24 populations of M. sinensis.
Population IdentitySample SizeRegionAltitude (m)Latitude (N)Longitude (E)Habital
Pop115Ya’an67729°58'39.3''102°59'24.5''Glade at hillside
Pop213Bi Feng Xia98930°07'25.5''102°59'48.6''Highway side
Pop312Bao Xing125330°16'05.7''102°49'19.5''River beach
Pop413Erlang Mountain209129°51'19.8''102°18'58.3''Glade at hillside
Pop511Tuowu Mountain163028°59'52.9''102°18'12.9''Glade at hillside
Pop68Niba Mountain163629°39'46.1''102°36'25.0''Glade at hillside
Pop711Renshou47130°01'05.9''103°58'21.8''Hillside
Pop810Hongya49329°51'22.6''103°14'03.5''Dam
Pop98Zizhong35029°48'50.4''104°42'28.6''Glade in orangery
Pop1012Luzhou24128°51'01.9''105°18'19.9''Rice field ridge
Pop119Yibin31728°45'15.4''104°36'48.5''Shrub at riverside
Pop125Zigong35329°24'21.9''104°49'01.4''Grassland
Pop1315Jiangyou68731°58'06.8''105°04'38.4''Highway slope
Pop145Jian’ge61132°13'25.0''105°35'17.9''Shrub at hillside
Pop1518Guangyuan66832°39'56.5''105°56'21.4''Shrub at hillside
Pop1614Daying32730°36'32.3''105°13'59.6''Shrub
Pop1716Banan47629°25'20.6''106°34'37.5''Forest edge at hillside
Pop1811Nanchuan57929°10'09.3''107°06'44.1''Shrub at hillside
Pop198Dabai45528°32'51.8''106°51'09.6''Highway slope
Pop2015Zunyi91427°59'11.5''106°52'25.1''Coniferous edge
Pop2112Guiyang126826°28'57.2''106°27'35.8''Bare rock
Pop226Zhenning128426°04'49.9''105°46'55.9''Glade
Pop236Huangguoshu94625°58'43.6''105°39'47.1''Forest edge
Pop247Yuxi172124°11'53.2''102°28'29.9''Hillside
Total number of individuals260

3.2. DNA Extraction

Fresh young leaves from each sampled individual were collected and dried by desiccant (silicagel self indicator). Genomic DNA was extracted from the dried leaves using the Plant Genomic DNA kit (Tiangen®, Beijing, China) according to the manufacturer’s protocol. The quality and concentration of the DNA were determined by comparing the sample with known standards of lambda DNA on 0.8% (w/v) agarose gels. The isolated genomic DNA was diluted to 20 ng/μL and stored at −20 °C for PCR amplification.

3.3. Primer Selection and PCR-SRAP Amplification

SRAP primer sequences (Li and Qurios) [20] used in this study were synthesized by Shanghai Sangon Biological Engineering Technology & Service (Shanghai, China). For PCR amplification, the total volume of each PCR reaction was 20 μL, which contains 3 μL template DNA (20 ng/μL), 10 μL of Mix (10× reaction buffer, 2.0 mM Mg2+, 0.6 mM of each dNTPs, Tiangen), 0.8 μL primers (10 pmol/μL), 0.4 μL Golden DNA Polymerase (2.5 U/μL, Tiangen®) and 5 μL of ddH2O. Amplification was performed on a Peltier Thermal Cycler (DNA Engine®, Bio-Rad, Hercules, CA, USA) under the following conditions: 5 min at 94 °C, followed by 5 cycles at 94 °C for 1 min, 35 °C for 1 min, and 72 °C for 1 min, and then 35 cycles at 94 °C for 1 min, 50 °C for 1 min, and 72 °C for 1 min, extended at 72 °C for 10 min, then stored at 4 °C. The SRAP fragments were separated on 6% denatured polyacrylamide gels (acrylamide: bis-acrylamide 19:1, 1× TBE) and electrophoresis, later the gel were stained by AgNO3 solution and photographed by the Gel Doc XR system (Bio-Rad).
Molecules 19 12881 g003 550
Figure 3. The geographical distribution of 24 populations of M. sinensis used in this study. The accessions were mainly sampled from four provinces, Sichuan, Chongqing, Guizhou and Yunnan in China. The different colors pentagram represents the five subgroups generated by STRUCTURE V2.3.3 software.
Figure 3. The geographical distribution of 24 populations of M. sinensis used in this study. The accessions were mainly sampled from four provinces, Sichuan, Chongqing, Guizhou and Yunnan in China. The different colors pentagram represents the five subgroups generated by STRUCTURE V2.3.3 software.
Molecules 19 12881 g003

3.4. Data Analysis

For the statistical analysis, the SRAP banding patterns which could be unambiguously scored across all the sampled populations were recorded manually for band presence (1) or absence (0), each of them was treated as an independent character regardless of its intensity. The discriminatory power of different SRAP primers was evaluated by means of polymorphic information content (PIC) [53]. The resulting present/absent data matrix was analyzed using POPGENE32 v.1.31 [54]. Assuming Hardy-Weinberg equilibrium, the genetic diversity was evaluated with three parameters: the percentage of polymorphic loci (P), Nei’s [31] gene diversity (H) and Shannon’s Information Index of Diversity (I). The total gene diversity was given as (HT) which was divided into gene diversity within populations (HS) and the gene diversity among populations (DST). These parameters were related according to the equation HT = HS + DST. The genetic differentiation coefficient (GST) was calculated as a ratio of DST/HT, which was used to measure the population differentiation. The genetic distance (GD) among 24 populations were also computed using the same program [43]. Gene flow was calculated as Nm = 0.5(1 − GST)/GST to estimate the level of gene drift among the populations [55]. Population structure of the 260 M. sinensis individuals was performed using STRUCTRE v2.3.4 software [56] with the ‘‘admixture model’’, burn-in period of 10,000 iterations and a run of 100,000 replications of Markov Chain Monte Carlo (MCMC) after burn in. For each run, 10 independent runs of STRUCTURE were performed with the number of clusters (K) varying from 1 to 11. Maximum likelihood and delta K (△K) values were used to determine the optimum number of subgroups [56,57]. For clustering analysis, the similarity coefficients were used to construct UPGMA (unweighted pair group method with arithmetic means) dendogram using SAHN (Sequential Agglomerative Hierarchical and Nested Clustering) module in the NTSYS-pc version2.10 software [58]. Genetic relationships among different M. sinensis populations were estimated using the Unweighted Pair-group Method with Arithmetic mean (UPGMA) cluster analysis based on the GD matrix. Analysis of molecular variance (AMOVA) was used to calculate variation among and within population using GenAlEx ver.6.41 [59].

4. Conclusions

SRAP markers were proved as useful tools in genetic diversity detection and population structure analysis. The 33 SRAP markers generated 688 bands with 646 as polymorphic bands. The average percentage of polymorphic bands (P), gene diversity (H), and Shannon’s diversity index (I) are 93.90%, 0.3377 and 0.5032 at species level respectively, indicating high level of genetic diversity. The mean genetic differentiation coefficient (Gst = 0.2326) estimated from 688 bands indicated that the larger genetic variation was found within populations which is consistent with the results calculated by the AMOVA analysis. In addition, there was a high frequency of gene flow (Nm = 1.6493) between populations, indicating there were more than one effective immigrant from one population into another at each generation. The population structure and phylogenetic analysis revealed five groups. Southwest China is located in one of the biodiversity hotspots of the world and the climate is variable. Additionally, M. sinensis is a cross-pollination plant, having complex genetic background and high heterozygosities. Hence, the genetic diversity and population structure analysis in the work reported here will facilitate genetic improvement and cultivar development with desired traits in further M. sinensis breeding programs.

Supplementary Materials

Supplementary materials can be accessed at: https://www.mdpi.com/1420-3049/19/8/12881/s1.

Supplementary File

Supplementary File 1

Acknowledgments

This work was supported by the National High-Technology Research and Development Program (863 Program) of China (No. 2012AA101801-02), the Earmarked Fund for the Modern Agro-Industry Technology Research System (#CARS-35-05) and the spring plan of Ministry of Education.

Author Contributions

Xin-Quan Zhang, Lin-Kai Huang, Xiao Ma and Yun-Wei Zhang conceived the project and designed the experiments. Gang Nie, Wen-Zhi Xu and Yan-Hong Yan performed the experiment. Gang Nie, Jian-Ping Wang and Hai-Dong Yan wrote the paper. All authors discussed the results and commented on the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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  • Sample Availability: Samples of the compounds are available from the authors.

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MDPI and ACS Style

Nie, G.; Zhang, X.-Q.; Huang, L.-K.; Xu, W.-Z.; Wang, J.-P.; Zhang, Y.-W.; Ma, X.; Yan, Y.-H.; Yan, H.-D. Genetic Variability and Population Structure of the Potential Bioenergy Crop Miscanthus sinensis (Poaceae) in Southwest China Based on SRAP Markers. Molecules 2014, 19, 12881-12897. https://doi.org/10.3390/molecules190812881

AMA Style

Nie G, Zhang X-Q, Huang L-K, Xu W-Z, Wang J-P, Zhang Y-W, Ma X, Yan Y-H, Yan H-D. Genetic Variability and Population Structure of the Potential Bioenergy Crop Miscanthus sinensis (Poaceae) in Southwest China Based on SRAP Markers. Molecules. 2014; 19(8):12881-12897. https://doi.org/10.3390/molecules190812881

Chicago/Turabian Style

Nie, Gang, Xin-Quan Zhang, Lin-Kai Huang, Wen-Zhi Xu, Jian-Ping Wang, Yun-Wei Zhang, Xiao Ma, Yan-Hong Yan, and Hai-Dong Yan. 2014. "Genetic Variability and Population Structure of the Potential Bioenergy Crop Miscanthus sinensis (Poaceae) in Southwest China Based on SRAP Markers" Molecules 19, no. 8: 12881-12897. https://doi.org/10.3390/molecules190812881

APA Style

Nie, G., Zhang, X. -Q., Huang, L. -K., Xu, W. -Z., Wang, J. -P., Zhang, Y. -W., Ma, X., Yan, Y. -H., & Yan, H. -D. (2014). Genetic Variability and Population Structure of the Potential Bioenergy Crop Miscanthus sinensis (Poaceae) in Southwest China Based on SRAP Markers. Molecules, 19(8), 12881-12897. https://doi.org/10.3390/molecules190812881

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